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• W2951275385 abstract "Raman microscopy is a valuable tool for detecting physical and chemical properties of a sample material. When probing nanomaterials or nanocomposites the spatial resolution of Raman microscopy is not always adequate as it is limited by the optical diffraction limit. Numerical post-processing with super-resolution algorithms provides a means to enhance resolution and can be straightforwardly applied. The aim of this work is to present interior-point least squares (IPLS) as a powerful tool for super-resolution in Raman imaging through constrained optimisation. IPLS's potential for super-resolution is illustrated on numerically generated test images. Its resolving power is demonstrated on Raman spectroscopic data of a polymer nanowire sample. Comparison to AFM data of the same sample substantiates that the presented method is a promising technique for analysing nanomaterial samples." @default.
• W2951275385 created "2019-06-27" @default.
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• W2951275385 date "2019-02-14" @default.
• W2951275385 modified "2023-09-27" @default.
• W2951275385 title "Sub-micron spatial resolution in far-field Raman imaging via positivity constrained super-resolution" @default.
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• W2951275385 hasPublicationYear "2019" @default.
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